How to build a billion+ dollar business in big data: the Palantir case study

Joe Lonsdale (co-founder of Palantir, Addepar and Formation8)  kicked off a meaningful conversation with us on building  multi-billion dollar businesses in big data at one of our recent Lightspeed Dinner Series events this week.

Drawing on examples from Palantir, Joe talked about his views on 1. Smart Enterprise, 2. Platform Effects and 3. Network Effects as related to big data.

1. Smart Enterprise is about data being at the center of your business. This is part of a series of shifts showing the value of data increasing over time in the context of the enterprise.

We share his view that the value and complexity of data is growing exponentially and most industries today all ill-equipped to handle this new reality and the rate and scale of enterprise data growth. Specifically, you need to get the data to the end-points in the organization as autonomously as possible so every person can make “smart” decisions in context. Organizations that do this effectively will gain advantages over ones that rely on a traditional workflows to manage information and productivity.

Joe elaborates on Smart Enterprise as an investment thesis for his new fund, Formation 8 (http://formation8.com/resources/the-smart-enterprise-wave/).

2. Building a Platform for solving complex problems gets exponentially harder. When the problem space is complex you arrive at solutions fastest through a mix of software and people engineering.  Algorithms alone don’t cut it.   Joe believes this is one of Palantir’s unique advantages and something they executed on well.

Palantir has been able to repeatedly pair  it’s core analytics platform with human investigators who  unlock business value across a variety of vertical domains. Their software and the residual know-how in the teams combine to form a powerful solution platform. The challenge ahead lies in translating this technology + human solution into a product that can be distributed through established sales channels for maximum scale. See Peter’s post related to this concept of repeatability  (http://blogs.wsj.com/accelerators/2013/10/01/peter-nieh-focus-on-repeatability). 

3. Network effects of knowledge are strong in the enterprise. Network effects, especially social, are a key strategy in the consumer space and at first glance, they don’t appear to apply to the world of Palantir.

However, on closer examination Joe demonstrates some great examples of how collaboration network effects can be even stronger when it comes to knowledge in the enterprise. For example, Government intelligence departments function as separate teams.  But when one team achieved an analysis breakthrough with Palantir, demand for their solution from the  adjacent intelligence groups followed very quickly. Often it was not just teams within the same agency but across multiple agencies and even across multiple allied governments.

When we tie  this back to the emergence of the Smart Enterprise it suggests that big data platforms and products a likely to have strong “knowledge network” effects that accrue to the market leading  players. As information and data insight become increasingly central to business effectiveness and competitive advantage it’s increasingly about ‘what you know’ (and how fast you know it).

We received a lot of great feedback on the dinner (thank you to all the attendees!).  Its clear  we need to have more of these types of conversation and we plan to do so frequently.  The guests for dinner included public and startup company executives, founders, investors and thought leaders in big data.

At Lightspeed we enjoy this type of discourse and appreciated the opportunity to hear  Joe’s views.  We  look forward seeing how these ideas play out in the future!

Thanks again,  Ravi Mhatre, Lightspeed Venture Partners

If you’re interested in learning more follow Ravi Mhatre at @rmtacct,   Lightspeed Ventures at @lightspeedvp and Lyon Wong at @lyonwong